Abstract 5451: Multiplex immunofluorescence for cancer research
Authors: Patrick Savickas, Sharwari Phanse
Journal: Cancer Research (2023)

Abstract Multiplex Immunofluorescence (M-IF) is a technique where multiple antibodies are visualized using unique fluorophores on the same slide. Thus, instead of employing panels of separately stained IHC slides that only reveal regional localization, it enables direct visualization of numerous proteins of interest on the same cell. This enables researchers and clinicians to comprehend precise interactions taking place at the cellular level in their tissue. The challenge of figuring out how to individually link markers with fluorophores without incurring cross contamination has hindered the development of M-IF assays. The first traditional approach was to ensure each marker was generated from a unique host species, and then use secondary antibodies against those host species conjugated to unique fluorophores. As a result, the unique host species that an antibody could be generated in were exhausted forcing the researchers to reach into exotic species. The second generation of technologies attempted to temporally solve this problem by sequentially staining the markers and then stripping off the antibody in between steps; preserving the fluorophores. This system leveraged the interaction of tyramide attached to a fluorophore and its affinity for tyrosine residues in tissue to form a stronger bond then the antibody to the tissue to endure the harsh striping step. This allowed the usage of multiple antibodies from the same host species but added antigen sheltering as the confounding variable due to crowding and exhaustion of antigenic sites. The latest generation technology we are using attempts to solve this linkage problem with DNA barcoding. A lock and key mechanism wherein the primary antibody is pre-conjugated with a unique barcode and the fluorophore with a corresponding inverse barcode. In this technique the primary antibodies can be applied as a cocktail in parallel to the tissue with the dna based linkage easily and gently broken when necessary. We then took this novel technique and applied it in a shotgun approach using Tissue Microarrays (TMAs) to screen against dozens of cores from breast, endometrial, carcinoma and melanoma cases. We then use Inform software to algorithmically categorize each cell and R-Studio to statically prove a significant coefficient of variation. This creates the ability to build panels for signatures that answer key research questions like “Where are the immune cells in the tissue microenvironment” and “is the tumor hot or cold? Activated, exhausted or proliferating?”. This abstract contrasts the operation of the new technology with the earlier approaches and will demonstrate how artificial intelligence-assisted algorithms can analyze and produce statistically significant datasets for cancer researchers. Citation Format: Patrick Savickas, Sharwari Phanse. Multiplex immunofluorescence for cancer research. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5451.